Physiological measures are increasingly used in many different areas of human-computer interaction (HCI) to infer knowledge about the affective and cognitive states of users. Technology currently available allows various physiological signals reflecting physiological measures to be sensed from users. For example, but without being limitative, the physiological signals may include (1) sweating rates measured from electrical conductance of the skin by an Electro Dermal Activity (EDA) sensor, (2) pulse rates measured from pulse sensor and/or (3) brain activity measured by electroencephalogram (EEG) electrodes to be placed on a user's scalp to detect brain waves of the user. The recent developments now allow to access physiological signals from wearable technologies, such as, for example, connected watches, which may include various sensors, such as, for example, (1) EDA sensors and/or (2) pulse sensors.
Once acquired, the physiological signals may be processed to serve various purposes. For example, physiological measures may be used in video games studies to measure boredom and/or game experience. Various applications may also be envisioned, including, but not limited to, providing intelligent tutoring systems leveraging physiological signals to improve adaptation of pedagogical interventions to user needs during learning sessions. Other applications may also be envisioned and may become apparent to the person skilled in the art of the present technology.
Even though various developments have been recently made in the field of inferring knowledge about the affective and cognitive states of users, improvements remain desirable as the analysis of physiological measures to extract meaningful information remains a challenge. In particular, extracting meaningful information from physiological signals typically requires expert knowledge which, in at least some instances, may not even be sufficient to associate physiological signals with user behaviour and/or assess, with a metric, a user state based on such physiological signals.